---
title: "Client Pilot Data Spring 2020"
output:
flexdashboard::flex_dashboard:
orientation: columns
social: menu
source_code: embed
vertical_layout: scroll
theme: cerulean
---
```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(rio)
library(here)
library(colorblindr)
library(gghighlight)
library(forcats)
library(ggrepel)
library(gt)
library(knitr)
library(kableExtra)
library(reactable)
library(plotly)
library(patchwork)
opts_chunk$set(echo = FALSE,
fig.width = 5,
fig.height = 6)
theme_set(theme_minimal(base_size = 8))
outcome <- import(here("data", "client_data_outcome.sav"),
setclass = "tbl_df") %>%
characterize() %>%
janitor::clean_names()
rm_prge <- import(here("data", "repeated_measures_prge.sav"),
setclass = "tbl_df") %>%
characterize() %>%
janitor::clean_names()
head(outcome)
head(rm_prge)
```
# PRGE Outcome Measures
Column {data-width=650}
-----------------------------------------------------------------------
```{r outcome measures data organization, include=FALSE}
head(outcome)
brief <- outcome %>%
filter(client == "PRGE") %>%
select(1, c(16:31))
brief_prge <- brief %>%
select(client, brief_eri_pre_self, brief_eri_post_self, brief_eri_pre_inf, brief_eri_post_inf)
brief_tidy <- brief_prge %>%
rename("Self Pre ERI" = brief_eri_pre_self,
"Self Post ERI" = brief_eri_post_self,
"Parent Pre ERI" = brief_eri_pre_inf,
"Parent Post ERI" = brief_eri_post_inf) %>%
pivot_longer(
cols = c(2:5),
names_to = "measure",
values_to = "score"
)
class <- outcome %>%
filter(client == "PRGE") %>%
select(client, class_total_pre, class_total_post) %>%
rename("Pre Score" = class_total_pre,
"Post Score" = class_total_post)
class_tidy <- class %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
symptoms <- outcome %>%
filter(client == "PRGE") %>%
select(1, c(6:13)) %>%
rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
"Feeling Slow Post" = pcss_post_feeling_slow,
"Feeling Foggy Pre" = pcss_pre_feeling_foggy,
"Feeling Foggy Post" = pcss_post_feeling_foggy,
"Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
"Difficulty Concentrating Post" = pcss_post_difficulty_concentrating,
"Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
"Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>%
pivot_longer(
cols = c(2:9),
names_to = "measure",
values_to = "score"
)
hit <- outcome %>%
filter(client == "PRGE") %>%
select(client, hit_pre, hit_post) %>%
rename("Pre Score" = hit_pre,
"Post Score" = hit_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
```
```{r outcome plots, include=FALSE}
#geom_rect(aes(xmin = -Inf, xmax = Inf, ymin = 65, ymax = 100),
#fill = "lightgreen") + #insert before geom_col
prge_brief <- c("Self Pre ERI",
"Self Post ERI",
"Parent Pre ERI",
"Parent Post ERI")
class_positions <- c("Pre Score", "Post Score")
pcss_positions <- c("Difficulty Remembering Post",
"Difficulty Remembering Pre",
"Difficulty Concentrating Post",
"Difficulty Concentrating Pre",
"Feeling Foggy Post",
"Feeling Foggy Pre",
"Feeling Slow Post",
"Feeling Slow Pre")
hit_positions <- c("Pre Score", "Post Score")
p1 <- ggplot(brief_tidy, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = prge_brief) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Emotion Regulation Index",
caption = "T-scores Above 65 are Clinically Significant")
p1
p2 <- ggplot(class_tidy, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = class_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "CLASS Scores")
p2
p3 <- ggplot(symptoms, aes(measure, score)) +
geom_hline(yintercept = 30,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = pcss_positions) +
scale_y_continuous(limits = c(0, 6),
breaks = c(0, 1, 2, 3, 4, 5, 6)) +
coord_flip() +
geom_text(aes(measure, score, label = score),
nudge_y = -0.5,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "PCSS Results",
subtitle = "Cognitive Symptoms",
caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms")
p3
p3a <- ggplot(hit, aes(measure, score)) +
geom_hline(yintercept = 50,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = hit_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "HIT Results",
caption = "Scores of 50 or Greater Suggest Headaches Impact Daily Functioning")
p3a
```
```{r prge brief, include=TRUE, fig.width=6}
p1
```
```{r prge class, include=TRUE, fig.width=6}
p2
```
Column {data-width=350}
-----------------------------------------------------------------------
```{r prge pcss, include=TRUE}
p3
```
```{r prge hit, include=TRUE}
p3a
```
# PRGE Repeated Meausures
Column {data-width=650}
-----------------------------------------------------------------------
```{r repeated measures data cleaning, include=FALSE}
head(rm_prge)
track <- rm_prge %>%
select(session, status)
p4 <- ggplot(track, aes(session, status)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 6),
breaks = c(1, 2, 3, 4, 5, 6)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Times Required to Reread Content",
title = "Status Tracking Goal")
p4
effort_data <- rm_prge %>%
select(session, effort)
p5 <- ggplot(effort_data, aes(session, effort)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 4),
breaks = c(1, 2, 3, 4)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Effort During Reading",
title = "Perceived Effort While Reading",
caption = "1 = No Effort at All\n 2 = Not Much Effort\n 3 = Some Effort\n 4 = A Lot of Effort")
p5
helpfulness <- rm_prge %>%
select(session, help)
p6 <- ggplot(helpfulness, aes(session, help)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Helpfulness",
title = "Perceived Helpfulness of Reading Strategies",
caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful")
p6
```
```{r status, include=TRUE, fig.align="left"}
p4
```
Column {data-width=350}
-----------------------------------------------------------------------
```{r effort, include=TRUE, fig.align="left"}
p5
```
```{r helpfulness, include=TRUE, fig.align="left"}
p6
```
# FALO Outcome Measures
Column {data-width=650}
-----------------------------------------------------------------------
```{r falo measures data organization, include=FALSE}
head(outcome)
falo <- outcome %>%
filter(client == "FALO")
brief_falo <- falo %>%
select(client, brief_cri_pre_self, brief_cri_post_self, brief_cri_pre_inf, brief_cri_post_inf) %>%
rename("Self Pre CRI" = brief_cri_pre_self,
"Self Post CRI" = brief_cri_post_self,
"Parent Pre CRI" = brief_cri_pre_inf,
"Parent Post CRI" = brief_cri_post_inf) %>%
pivot_longer(
cols = c(2:5),
names_to = "measure",
values_to = "score"
)
class_falo <- falo %>%
select(client, class_total_pre, class_total_post) %>%
rename("Pre Score" = class_total_pre,
"Post Score" = class_total_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
pcss_falo <- falo %>%
select(1, c(6:13)) %>%
rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
"Feeling Slow Post" = pcss_post_feeling_slow,
"Feeling Foggy Pre" = pcss_pre_feeling_foggy,
"Feeling Foggy Post" = pcss_post_feeling_foggy,
"Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
"Difficulty Concentrating Post" = pcss_post_difficulty_concentrating,
"Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
"Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>%
pivot_longer(
cols = c(2:9),
names_to = "measure",
values_to = "score"
)
hit_falo <- falo %>%
select(client, hit_pre, hit_post) %>%
rename("Pre Score" = hit_pre,
"Post Score" = hit_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
```
```{r falo plots, include=FALSE}
falo_brief_graph <- c("Self Pre CRI",
"Self Post CRI",
"Parent Pre CRI",
"Parent Post CRI")
p7 <- ggplot(brief_falo, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = falo_brief_graph) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Cognitive Regulation Index",
caption = "T-scores Above 65 are Clinically Significant")
p7
p8 <- ggplot(class_falo, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = class_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "CLASS Scores")
p8
p9 <- ggplot(pcss_falo, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = pcss_positions) +
scale_y_continuous(limits = c(0, 6),
breaks = c(0, 1, 2, 3, 4, 5, 6)) +
geom_text(aes(measure, score, label = score),
nudge_y = -1,
color = "white") +
coord_flip() +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "PCSS Results",
subtitle = "Cognitive Symptoms",
caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms")
p9
falo_pcss_table <- pcss_falo %>%
select(-client) %>%
gt() %>%
cols_label(measure = "PCSS Question",
score = "Response") %>%
cols_align(align = "left", columns = vars(measure)) %>%
cols_align(align = "center", columns = vars(score)) %>%
tab_header(title = "PCSS Results",
subtitle = "Cognitive Symptoms")
falo_pcss_table
falo_reactable <- pcss_falo %>%
select(-client) %>%
rename("PCSS Question" = measure,
"Response" = score) %>%
reactable()
falo_reactable
p10 <- ggplot(hit_falo, aes(measure, score)) +
geom_hline(yintercept = 50,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = hit_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "HIT Results",
caption = "Scores of 50 or Greater Suggest Headaches Significantly Impact Daily Functioning")
p10
```
```{r falo brief, include=TRUE, fig.width=6}
p7
```
```{r falo class, include=TRUE, fig.width=6}
p8
```
Column {data-width=350}
-----------------------------------------------------------------------
```{r falo pcss, include=TRUE}
falo_reactable
```
```{r falo hit, include=TRUE}
p10
```
# DRKAT Outcome Measures
Column {data-width=650}
-----------------------------------------------------------------------
```{r drkat measures data organization, include=FALSE}
head(outcome)
drkat <- outcome %>%
filter(client == "DRKAT")
brief_drkat <- drkat %>%
select(1, 16, 17, 20, 21, 32, 33) %>%
rename("Pre Global" = brief_global_pre_self,
"Post Global" = brief_global_post_self,
"Pre BRI" = brief_bri_pre_self,
"Post BRI" = brief_bri_post_self,
"Pre MI" = brief_mi_pre_self,
"Post MI" = brief_mi_post_self) %>%
pivot_longer(
cols = c(2:7),
names_to = "measure",
values_to = "score"
)
drkat_brief_graph <- c("Pre Global",
"Post Global",
"Pre BRI",
"Post BRI",
"Pre MI",
"Post MI")
class_drkat <- drkat %>%
select(client, class_total_pre, class_total_post) %>%
rename("Pre Score" = class_total_pre,
"Post Score" = class_total_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
pcss_drkat <- drkat %>%
select(1, c(6:13)) %>%
rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
"Feeling Slow Post" = pcss_post_feeling_slow,
"Feeling Foggy Pre" = pcss_pre_feeling_foggy,
"Feeling Foggy Post" = pcss_post_feeling_foggy,
"Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
"Difficulty Concentrating Post" = pcss_post_difficulty_concentrating,
"Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
"Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>%
pivot_longer(
cols = c(2:9),
names_to = "measure",
values_to = "score"
)
hit_drkat <- drkat %>%
select(client, hit_pre, hit_post) %>%
rename("Pre Score" = hit_pre,
"Post Score" = hit_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
```
```{r drkat plots, include=FALSE}
drkat_brief_plot <- ggplot(brief_drkat, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = drkat_brief_graph) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Self-Report Global Index, Behavioral Regulation Index, & Metacognitive Index",
caption = "T-scores Above 65 are Clinically Significant")
drkat_brief_plot
drkat_class_plot <- ggplot(class_drkat, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = class_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "CLASS Scores")
drkat_class_plot
drkat_pcss_plot <- ggplot(pcss_drkat, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = pcss_positions) +
scale_y_continuous(limits = c(0, 6),
breaks = c(0, 1, 2, 3, 4, 5, 6)) +
geom_text(aes(measure, score, label = score),
nudge_y = -1,
color = "white") +
coord_flip() +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "PCSS Results",
subtitle = "Cognitive Symptoms",
caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms")
drkat_pcss_plot
drkat_hit_plot <- ggplot(hit_drkat, aes(measure, score)) +
geom_hline(yintercept = 50,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = hit_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "HIT Results",
caption = "Scores of 50 or Greater Suggest Headaches Significantly Impact Daily Functioning")
drkat_hit_plot
```
```{r drkat brief, include=TRUE, fig.width=6}
drkat_brief_plot
```
```{r drkat class, include=TRUE, fig.width=6}
drkat_class_plot
```
Column {data-width=350}
-----------------------------------------------------------------------
```{r drkat pcss, include=TRUE}
drkat_pcss_plot
```
```{r drkat hit, include=TRUE}
drkat_hit_plot
```
# Client Demographics
Column {data-width=650}
-----------------------------------------------------------------------
```{r demographic info, include=FALSE}
head(outcome)
demo <- outcome %>%
select(1:5)
head(demo)
demo_table <- demo %>%
gt() %>%
cols_label(client = "Client",
sex = "Sex",
age = "Age",
prev_mtbi = "Prior Concussions",
hx_depression = "History of Depression/Anxiety") %>%
cols_align(align = "left", columns = vars(client)) %>%
cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>%
tab_header(title = "Client Demographics")
demo_table
```
```{r demographic table, include=TRUE, fig.width=6}
demo_table
```
